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Titlebook: Seasonal Climate: Forecasting and Managing Risk; Alberto Troccoli,Mike Harrison,Simon J. Mason Conference proceedings 20081st edition Spri

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書目名稱Seasonal Climate: Forecasting and Managing Risk
編輯Alberto Troccoli,Mike Harrison,Simon J. Mason
視頻videohttp://file.papertrans.cn/864/863086/863086.mp4
概述First unified reference ‘textbook’ in seasonal to interannual climate predictions and their practical uses.Embraces prediction of El Ni?o and management of climate risks.Covers a rapidly-developing sc
叢書名稱NATO Science Series: IV:
圖書封面Titlebook: Seasonal Climate: Forecasting and Managing Risk;  Alberto Troccoli,Mike Harrison,Simon J. Mason Conference proceedings 20081st edition Spri
描述.Originally formed around a set of lectures presented at a NATO Advanced Study Institute (ASI), this book has grown in scope and in aspiration to become organised and presented rather more as a textbook than as a standard “collection of proceedings”. The lack of a unified reference textbook covering both the science of seasonal to interannual predictions and real-world uses of the forecasts was the main driver for the effort placed into writing an amalgamated introductory book, each chapter of which has been thoroughly peer reviewed. Throughout, our objective has been to present a book accessible to people from diverse disciplines, both scientific and social, interested in this intriguing and fast emerging area...The fascination of seasonal climate forecasting, for which El Ni?o forecasting provides the prime basis, derives from its multi-faceted character. Not only does it pose exciting new scientific challenges for the climate community, but it is linked naturally to a great variety of key practical concerns, from security related issues, such as water resource management, food security, and disaster prediction and prevention, to health planning, agriculture management, energy su
出版日期Conference proceedings 20081st edition
關(guān)鍵詞Climate Change; Earth; Environmental; NATO; Science; Sciences; Series IV; Sustainable Development; Water res
版次1
doihttps://doi.org/10.1007/978-1-4020-6992-5
isbn_softcover978-1-4020-6991-8
isbn_ebook978-1-4020-6992-5Series ISSN 1568-1238
issn_series 1568-1238
copyrightSpringer Science+Business Media B.V. 2008
The information of publication is updating

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1568-1238 t variety of key practical concerns, from security related issues, such as water resource management, food security, and disaster prediction and prevention, to health planning, agriculture management, energy su978-1-4020-6991-8978-1-4020-6992-5Series ISSN 1568-1238
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Statistical Modellingtistical model should be tested carefully on independent data. Most statistical models are based on linear regression, which provides a “best guess” forecast under the assumption that a given change in the value of a predictor results in a constant change in the expected value of the predictand rega
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From Dynamical Model Predictions to Seasonal Climate Forecastsl averages, downscaling may be required to make the forecast relevant for specific locations, and to provide more detailed information about the statistics of weather within the season. Commonly used spatial and temporal downscaling procedures are described. Some procedures for describing the uncert
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